


Sensing, AI and imagination: How vision is shaping the Internet of Things
Vision is quickly becoming the leading sensing application in the development of the Internet of Things, which is profoundly changing our world.
Think about factories and manufacturing. Computer vision systems can transform modern factories by ensuring quality control, optimizing processes, reducing waste and driving continuous improvement. These systems help improve productivity, cost-effectiveness, and competitiveness of manufacturing operations.
In a recent Arm IoT survey, industrial respondents said the two main reasons they are adopting IoT technologies are to improve their use of data to change business decisions and improve customer experience. In commercial construction, a similar revolution is underway.
Building and IoT Vision Sensors
Building managers are leveraging IoT visual sensing technology to monitor and analyze activity inside buildings to improve space usage efficiency. By collecting and analyzing foot traffic data, office and work area occupancy, they are able to better plan office space layout and seating arrangements, as well as effectively allocate meeting room resources. This smart monitoring system gives them a more accurate picture of how different areas of the building are being used, allowing them to make more informed decisions and increase productivity and employee satisfaction.
Construction and factory managers have been thinking about outcomes like this since the dawn of digitalization, but what is happening now to help them realize their ambitions? What motivates developers to adopt visual sensing solutions so quickly and with such ingenious results?
Utilize efficient, low-power processing technology to process large amounts of data more effectively, and extend applications through artificial intelligence algorithms to achieve ultra-intelligent data processing.
CPUs and Neural Processors
The convergence of efficient CPUs and neural processors with artificial intelligence and machine learning software at the edge is opening up huge new business opportunities.
Surprisingly, it seems too early. I can't help but be reminded of the early days of the mobile phone industry: a rapidly forming ecosystem that enabled greater design flexibility and application development by abstracting software from hardware.
Anyone currently standing on the edge of visionary innovation risks being left behind. This isn't just about missed opportunities.
There is almost no reason not to take the initiative and get to work. Because the tools and processes needed to realize your personal vision are already in place and ready to go.
IoT Vision Sensing Considerations
Connectivity
Through Wi-Fi, Integrating connectivity into IoT devices through protocols such as Bluetooth Low Energy (BLE) has been a key development, similar to the integration of connectivity in smartphones.
Developers are free to choose the right communication protocol for their specific application. For example, smart vision systems in factories might take advantage of Wi-Fi's cost and scalability advantages, while developers building energy-hungry systems might choose BLE.
More far-reaching is the growing adoption of high-bandwidth 5G technology, which promises applications in smart cities. (Indeed, in a recent Arm survey of innovators, nearly half of respondents cited 5G as one of the factors that will have the biggest impact on IoT growth over the next five years).
Security
Security is a key issue in the Internet of Things - devices have been used in this field for many years - especially in imaging data aspect. IoT visual sensing continues to evolve, with challenges addressed through frameworks such as PSA Certified to ensure devices can be maintained and remain secure over the long term.
Machine Learning at the Edge
As more powerful and efficient processing is pushed from the cloud to the edge, machine learning applications are being deployed in new , a fascinating field. They are improving real-time performance and supporting the development of new solutions.
Standards
Common underlying APIs and frameworks (such as Trusted Firmware) enable developers to address core functionality consistently across multiple platforms, thereby promoting innovation and value addition. Thanks to the adoption of standards, fragmentation is becoming a thing of the past.
Seize the market
The journey of vision-based IoT systems from concept to reality has transformed in other ways. A generation of developers has grown up on open tools and platforms, like the Raspberry Pi.
Now, many developers (who first encountered technology like the Raspberry Pi as teenagers) are developing in the professional world. They demand the same easy-to-exploit experiences they had as teenagers.
All of these factors combine to spur innovation in vision-based applications, not only because the processing power and machine learning capabilities are already in place, but because the barriers to design and development are falling.
Imagine what could be achieved by installing an ML-enabled camera at the parking lot entrance (like we have at Arm’s Cambridge office). It can identify all vehicles entering and exiting throughout the day, eliminating the need to install sensors in every parking space within a building.
The capabilities of visual sensing in the Internet of Things have been significantly enhanced, and its diverse applications are truly fascinating. The sudden expansion of IoT capabilities enabled by vision technology is truly remarkable.
Early adopters win hearts and minds, but laggards (those waiting to see how early IoT adoption progresses) still have a huge opportunity to leverage vision technology to transform their businesses. You can see the possibilities. The only thing holding us back now is our imagination.
The above is the detailed content of Sensing, AI and imagination: How vision is shaping the Internet of Things. For more information, please follow other related articles on the PHP Chinese website!

Cyberattacks are evolving. Gone are the days of generic phishing emails. The future of cybercrime is hyper-personalized, leveraging readily available online data and AI to craft highly targeted attacks. Imagine a scammer who knows your job, your f

In his inaugural address to the College of Cardinals, Chicago-born Robert Francis Prevost, the newly elected Pope Leo XIV, discussed the influence of his namesake, Pope Leo XIII, whose papacy (1878-1903) coincided with the dawn of the automobile and

This tutorial demonstrates how to integrate your Large Language Model (LLM) with external tools using the Model Context Protocol (MCP) and FastAPI. We'll build a simple web application using FastAPI and convert it into an MCP server, enabling your L

Explore Dia-1.6B: A groundbreaking text-to-speech model developed by two undergraduates with zero funding! This 1.6 billion parameter model generates remarkably realistic speech, including nonverbal cues like laughter and sneezes. This article guide

I wholeheartedly agree. My success is inextricably linked to the guidance of my mentors. Their insights, particularly regarding business management, formed the bedrock of my beliefs and practices. This experience underscores my commitment to mentor

AI Enhanced Mining Equipment The mining operation environment is harsh and dangerous. Artificial intelligence systems help improve overall efficiency and security by removing humans from the most dangerous environments and enhancing human capabilities. Artificial intelligence is increasingly used to power autonomous trucks, drills and loaders used in mining operations. These AI-powered vehicles can operate accurately in hazardous environments, thereby increasing safety and productivity. Some companies have developed autonomous mining vehicles for large-scale mining operations. Equipment operating in challenging environments requires ongoing maintenance. However, maintenance can keep critical devices offline and consume resources. More precise maintenance means increased uptime for expensive and necessary equipment and significant cost savings. AI-driven

Marc Benioff, Salesforce CEO, predicts a monumental workplace revolution driven by AI agents, a transformation already underway within Salesforce and its client base. He envisions a shift from traditional markets to a vastly larger market focused on

The Rise of AI in HR: Navigating a Workforce with Robot Colleagues The integration of AI into human resources (HR) is no longer a futuristic concept; it's rapidly becoming the new reality. This shift impacts both HR professionals and employees, dem


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

Dreamweaver Mac version
Visual web development tools

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

SublimeText3 English version
Recommended: Win version, supports code prompts!

WebStorm Mac version
Useful JavaScript development tools
